Note: Some courses run the entire semester (example: Fall 1 and 2), others run only part of the semester (example: Spring 2), and some courses last only a few weeks. Review course details below and read the syllabus for more information.

This course will introduce students to the most commonly used qualitative methods for medical-related research. It will provide a foundation in the application of qualitative methods to medical and health research. Topics addressed will include uses of qualitative data, designing studies, sampling strategies, collecting data, and qualitative analysis. A variety of methods will be discussed, with an emphasis on using focus groups and various interviewing techniques. Students will learn the best practices in qualitative research and how to critically evaluate qualitative studies and articles. Upon completion of the course, students will be able to plan, conduct, and analyze a qualitative study. Course activities: lectures, discussion, article critiques, and paper.

The objective of this advanced graduate course is to prepare highly motivated students to perform health services research using administrative data. Lectures will provide tutorials on national administrative databases, review journal articles using these databases, instruction in SAS programming and application of health services research methods using administrative databases. Strengths and limitations of large databases that are commonly used for research will be considered, and special attention will be devoted to large federal databases that are readily available to new investigators. Students will learn how to obtain, link, and analyze large databases, understand the key issues related to data security and confidentiality, and become knowledgeable about key methodologic issues in observational studies using administrative data. Students will evaluate published studies based on large administrative databases, develop a health services research proposal and complete a short research project that uses administrative data.

Course note: You must contact the instructor two weeks prior to the start of class to discuss ideas for the class project; M19-501 and M21-560 are required prerequisites; SAS or SPSS software required.SyllabusM19-561 – Epidemiology of Psychiatric Disorders Across the LifespanFall 1 and 2; Fridays 1 to 4 p.m.A. Glowinski, K. Bucholz
3 credits

This course takes an integrated developmental approach to the epidemiology, etiology and evolving nosology of psychiatric disorders. The course is organized into four sections. Part I lays most of the conceptual groundwork needed to understand and plan research on psychiatric disorders and their risk factors in the general population. The next two sections mostly focus on the nosology, epidemiology and etiology of specific psychiatric disorders. Part II covers disorders that are traditionally considered child psychiatric disorders but have developmental consequences for adulthood and/or often persist chronically through adulthood. Part III covers psychiatric disorders more typical of adulthood as well as those that often emerge in adolescence or earlier but are more prevalent in adulthood. Finally, Part IV will be devoted to special topics in psychiatric and developmental epidemiology. By the end of the course, students with sufficient statistical background will be expected to design and conduct basic analyses of existing psychiatric epidemiologic data and others will be expected to conduct a literature review on a topic of their choice. Alternatively, students will have the option to prepare a poster submission and poster to submit to a meeting of their choice.

In this course, we will introduce students to the methods and applications of decision analysis and cost-effectiveness analysis in health care technology assessment, medical decision making, and health resource allocation. At the conclusion of the class, the student will have an understanding of the theoretical basis for economic evaluation and decision analysis, its application, and hands-on experience in the application of the methods. Among the topics covered are the development of a research question, choice of decision perspective, development of a decision analytic model, estimation of costs and benefits, use of preference based measures, addressing uncertainty and preparation of a manuscript presenting a decision analytic study.

This course covers statistical model development with explicitly defined hierarchies. Such multilevel specifications allow researchers to account for different structures in the data and provide for the modeling of variation between defined groups. The course begins with simple nested linear models and proceeds on to non-nested models, multilevel models with dichotomous outcomes, and multilevel generalized linear models. In each case, a Bayesian perspective on inference and computation is featured. The focus of the course will be practical steps for specifying, fitting, and checking multilevel models with much time spent on the details of computation in the R and bugs environments.

Course note: This course assumes knowledge of basic statistics as taught in a first year undergraduate or graduate sequence. Topics should include: probability, cross-tabulation, basic statistical summaries, and linear regression in either scalar or matrix form. Knowledge of R, basic matrix algebra and calculus is helpful. Syllabus and More InformationM19-5656 Global Burden of Disease: Methods and Applications Fall 1 and 2; Thursdays 1 to 4 p.m.R. Price, M. Schroff
3 credits

This transdisciplinary course provides an overview of the quantitative and qualitative methods and their applications for studying the global burden of diseases. The topics cover infectious diseases, non-communicable chronic medical illness and behavioral disorders. At the end of this course, students will have learned basic methods used for global health research and major trends in global burden of diseases; they will be able to apply the knowledge of measurements to forecast the future of the global burden of specific diseases of interest to develop needed policy recommendations. Students will be able to address prevention and intervention strategies targeted to specific nations or regions using a transdisciplinary approach. Students will have learned major dimensions of sociocultural and economic factors that affect global and regional distributions of major disease categories and how they are linked to global trade and economy in some instances. The transdisciplinary knowledge and hands-on skills learned from this course will assist students with an interest in international research to select a disease or underlying condition with a significant burden on the population of diverse nations or regions. Students will acquire practical skills that can be used in the health professions, including cultural competency training as it applies to medicine and public health. Course activities: Lectures, transdisciplinary class discussion and exercises, homework, and transdisciplinary team presentations.

A critical step in the dissemination of population-level clinical research is communicating research findings and key messages to the media and lay audiences. With conflicting messages coming from advocacy groups and others, the burden falls on the clinician-researcher to distill complex information, dispel misinformation, and tell a compelling story that resonates with the audience. The course will equip students with the skills, technique, experience and confidence needed to give successful, engaging media interviews and presentations related to the publication of research and expertise-specific topics. Through critique, tape and review exercises, class discussion, and guest speakers, students will learn all the facets that make an interview or presentation successful, including nonverbal communication and delivery skills (body language and vocal interpretation), content and messaging, and navigating interactions with the media. The instructor will evaluate each student’s skill set and create a working skills inventory on which the student will build throughout the course in a series of on-camera experiences.

This course will provide a comprehensive introduction to comparative effectiveness research. Topics include an overview of comparative effectiveness research, stakeholder engagement in comparative effectiveness research, designing comparative effectiveness research methodologic challenges in doing comparative effectiveness research, and recent developments in PCORI and Federal policy. Students will be expected to review and evaluate comparative effectiveness studies as well as actively participate in class discussions.

This course will provide a comprehensive introduction to principles of shared decision making and health literacy and their implications for clinical communication. Topics may include basic and applied research on shared decision making, principles of designing and evaluating patient decision aids, principles of health literacy, research on relationship between health literacy, numeracy, and health outcomes, best practices for communication with low-numerate and low-literate individuals, best practices (and controversies) in communicating probabilities and their associated uncertainty about screening and treatment outcomes, and best practices for designing and evaluating written information for clinical populations (such as intake forms, brochures, and informed consent documents). Course activities: lectures, manuscript critiques, class project, and paper.

This course introduces principles of patient safety, quality measurement and quality improvement. Classes are designed to provide students with hands-on skills in systems thinking and in preventing, learning from, and dealing with medical error and adverse events. Students will also learn fundamentals in approaches to evaluating quality, including quantitative methods in measure development. We will discuss various approaches and challenges to knowledge translation and effective change management in improving quality. Students will be encouraged to use their real-world experiences in problem solving around patient safety concerns, to develop and evaluate quality measures in their respective fields and to develop a quality improvement project in their area of interest as part of the course.

Introduction to the use of meta-analysis and related methods used to synthesize and evaluate epidemiological and clinical research in public health and clinical medicine. Concepts introduced and illustrated through case studies of public health and medical issues. Course activities: lectures, class discussion, group project, and paper.

This course will present an introduction to the methods of predictive modeling, with applications to both genetic and clinical data. Basic concepts and philosophy of supervised and unsupervised data mining as well as appropriate applications will be discussed. Topics covered will include multiple comparisons adjustment, cluster analysis, self-organizing maps, principal component analysis, and predictive model building through logistic regression, classification and regression trees (CART), multivariate adaptive splines (MARS), neural networks, random forests, and bagging and boosting. Approaches to validation will be discussed and strategies for estimation of added value with expanded variable lists will be a key focus of this applied quantitative methods course.

This course provides an overview of the principles of substance-related addictions and the processes and mechanisms that underlie addiction. Students will be introduced to the epidemiology and developmental course of addiction, risk and protective influences that act on the course of addiction and its adverse health consequences. Both genetic and environmental underpinnings will be discussed. The impact of policy and economics will be studied. Emerging addictive behaviors, effective interventions and treatment modalities will be discussed. Students will be expected to participate in class discussions, complete written assignments (review paper format) and present one of their written assignments via in-class presentation. Course activities: Lectures, class discussion, review paper presentation, and three short papers.

This course provides an introduction to dissemination and implementation (D&I) science (i.e., translational research in health). Topics include the importance and language of D&I science; designs, methods and measures; differences and similarities across clinical, public health and policy settings; selected tools for D&I research and practice; and future issues. Course activities: Lectures, class discussions, manuscript critiques, and class project (culminating in a poster).